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Abstract

Purpose: The goal of this study was to determine neck muscle forces and spinal loads that result from isometric muscle contractions.

Methods: Electromyographic (EMG) activity of the neck musculature and a three-dimensional biomechanical model of the neck were used. The model was EMG-based and estimated muscle forces and spinal loads at the C4/5 level. EMG signals were collected from eight sites at the C4/5 level of the neck using Ag-AgCl surface electrodes from 10 adult male subjects. The subjects performed isometric contractions gradually developing to maximum efforts in flexion, extension, left lateral bending, and right lateral bending.

Results: During maximum voluntary contraction (MVC) trials most muscles generated high levels of EMG signal during cervical rotation. The posterior surface of the neck (trapezius) was the only electrode site at which maximum activity EMG consistently occurred by the same method (rotation) in all subjects. Variations in the EMG patterns were observed in different experiments that produced overall neck moments of equal magnitudes. With these data the model computed variations in load distribution among the agonist muscles. Consistent also with EMG distributions, the model also computed co-contractions of antagonist muscles. The average (± SD) magnitudes of peak moments were 28.3 (± 3.3) Nm in extension, 17.7 (± 3.1) Nm in flexion, 16.9 (± 2.8) Nm in left lateral bending, and 17.0 (± 2.9) Nm in right lateral bending. The model predicted C4/5 joint compressive forces during peak moments were 1372 (± 140) N in extension, 1654 (± 308) N in flexion, 956 (± 169) N in left lateral bending, and 1065 (± 207) N in right lateral bending.

Injury of the cervical spine presents a number of diagnostic issues with frequent sites of cervical spinal injury at the C5 level (74%), C4 level (16%), and C6 level (10%) (27). The pathogenesis of neck pain, however, is often unknown (24). Generally, mechanical factors are involved in the cause of some neck pain. Thus, a better knowledge of the neck muscle forces and spinal loads imposed by the performance of physical tasks will help differentiate possible causes of neck pain. In addition, this knowledge will be useful for diagnostic, surgical, preventive, and rehabilitative medicine.

One of two possible approaches, the optimization technique or the EMG-based technique, is typically used to solve the statically indeterminate problem in biomechanical modeling of body segments. Although optimization models have proven useful in predicting muscle forces from intersegmental moments, some discrepancies between model predictions and empirical results exist. For example, some coefficients of linear correlation between predictions of a neck model and experimental results were 0.29 and 0.33 (16). A major weakness of optimization models is that they do not predict co-contraction of antagonistic muscles, yet the co-contraction of muscles developing opposing moments about a joint is a common experimental observation (11). The optimization models often predict muscles to be inactive in situations where significant EMG activity is observed (9,19,21,22).

The EMG-based approach, on the other hand, predicts co-contractions of antagonistic muscles together with the various patterns of agonistic synergy (13). The EMG-based approach is sensitive to subject and trial differences in the magnitudes of individual muscle forces needed to produce the same reaction moment. In contrast, the optimization method shows a similar estimate of muscle forces for all subjects and trials producing the same moment. The EMG-based model has proven to be a valuable method to determine muscle forces and spinal loads in the low back. For example, a dynamic model of the lumbar spine was used to estimate forces in active tissues using a myoelectrically based strategy and in passive structures from estimates of strain (12–14).

Several studies have investigated the effects of co-contraction with lumbar models. To evaluate the effects of co-contraction, Hughes et al. (8) applied K-K-T (Karush-Kuhn-Tucker) multipliers to a human lumbar optimization model. Their results showed that spinal compression can be increased substantially by co-contraction and that, in special circumstances, co-contraction may be able to decrease the spinal compression in a conventional torso optimization model that is used extensively in studies of the lumbar spine. Cholewicki et al. (3) myoelectrically examined antagonistic muscle co-contraction during slow trunk flexion and extension tasks around neutral posture. When mechanical stability criteria were considered, their inverted pendulum trunk model predicted trunk muscle co-contraction levels necessary to maintain spine stability that corresponded very well to their experimental results. In addition, they observed that antagonistic muscle co-contraction increased in response to increased axial load on the spine. Thelen et al. (26) used a myoelectric signal-muscle stress model and consecutive optimization routines to calculate muscle forces including co-contraction in a human lumbar spine model. To quantify the degree of co-contraction, they subdivided the predicted muscle forces into two sets, task-moment set and co-contraction set of muscle forces that produced zero net moment. Their analysis suggested that substantial contractions of lumbar muscles, especially during asymmetric exertions, are used for reasons other than equilibrating moments at the L3-L4 level.

To our knowledge, there have been no biomechanical models of the neck that have used an EMG-based approach and therefore no models that have considered the effects of antagonistic muscle forces on cervical spinal loading. Pursuant to these effects, the following hypotheses were tested in this study: 1) substantial levels of antagonistic co-contractions and variations in muscle activation are present in neck musculature of neutral posture during voluntary isometric efforts; 2) the EMG-based model predicts various muscle force distributions including antagonistic muscle forces that correspond to the cervical muscle activation patterns; 3) when including antagonistic muscle forces in an EMG-based model, estimates of spinal compressive loads are higher than previously reported.

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